




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


a_ :						str				 =			{"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTConfig""", """ViTOnnxConfig"""]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_ :						Union[str, Any]				 =			["""ViTFeatureExtractor"""]
     a_ :						Any				 =			["""ViTImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_ :						Tuple				 =			[
         """VIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """ViTForImageClassification""",
         """ViTForMaskedImageModeling""",
         """ViTModel""",
         """ViTPreTrainedModel""",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_ :						Union[str, Any]				 =			[
         """TFViTForImageClassification""",
         """TFViTModel""",
         """TFViTPreTrainedModel""",
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_ :						Tuple				 =			[
         """FlaxViTForImageClassification""",
         """FlaxViTModel""",
         """FlaxViTPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_vit import ViTFeatureExtractor
          from .image_processing_vit import ViTImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_vit import (
              VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
              ViTForImageClassification,
              ViTForMaskedImageModeling,
              ViTModel,
              ViTPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
     import sys

     a_ :						Optional[Any]				 =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










'''simple docstring'''







# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

lowerCAmelCase_     						=				'''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
    raise ImportWarning(
        '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
    )

if version.parse(pyarrow.__version__).major < 8:
    raise ImportWarning(
        '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
        '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
    )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

lowerCAmelCase_     						=				concatenate_datasets
lowerCAmelCase_     						=				DownloadConfig
lowerCAmelCase_     						=				DownloadManager
lowerCAmelCase_     						=				DownloadMode
lowerCAmelCase_     						=				DownloadConfig
lowerCAmelCase_     						=				DownloadMode
lowerCAmelCase_     						=				DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


